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Title: FPGA-Based Velocity Estimation for Control of Robots with Low-Resolution Encoders
Robot control algorithms often rely on measurements of robot joint velocities, which can be estimated by measuring the time between encoder edges. When encoder edges occur infrequently, such as at low velocities and/or with low resolution encoders, this measurement delay may affect the stability of closed-loop control. This is evident in both the joint position control and Cartesian impedance control of the da Vinci Research Kit (dVRK), which contains several low-resolution encoders. We present a hardware-based method that gives more frequent velocity updates and is not affected by common encoder imperfections such as non-uniform duty cycles and quadrature phase error. The proposed method measures the time between consecutive edges of the same type but, unlike prior methods, is implemented for the rising and falling edges of both channels. Additionally, it estimates acceleration to enable software compensation of the measurement delay. The method is shown to improve Cartesian impedance control of the dVRK.
Authors:
; ; ;
Award ID(s):
1637789
Publication Date:
NSF-PAR ID:
10075848
Journal Name:
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Sponsoring Org:
National Science Foundation
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